Improving Medical Research in the United Kingdom

Peer reviewedPublisher PD

Artificial intelligence in lung cancer diagnostic imaging: a review of the reporting and conduct of research published 2018–2019

Objective: This study aimed to describe the methodologies used to develop and evaluate models that use artificial intelligence (AI) to analyse lung images in order to detect, segment (outline borders of), or classify pulmonary nodules as benign or malignant. Methods: In October 2019, we systematically searched the literature for original studies published between 2018 and 2019 that described prediction models using AI to evaluate human pulmonary nodules on diagnostic chest images. Two evaluators independently extracted information from studies, such as study aims, sample size, AI type, patient characteristics, and performance. We summarised data descriptively. Results: The review included 153 studies: 136 (89%) development-only studies, 12 (8%) development and validation, and 5 (3%) validation-only. CT scans were the most common type of image type used (83%), often acquired from public databases (58%). Eight studies (5%) compared model outputs with biopsy results. 41 studies (26.8%) reported patient characteristics. The models were based on different units of analysis, such as patients, images, nodules, or image slices or patches. Conclusion: The methods used to develop and evaluate prediction models using AI to detect, segment, or classify pulmonary nodules in medical imaging vary, are poorly reported, and therefore difficult to evaluate. Transparent and complete reporting of methods, results and code would fill the gaps in information we observed in the study publications. Advances in knowledge: We reviewed the methodology of AI models detecting nodules on lung images and found that the models were poorly reported and had no description of patient characteristics, with just a few comparing models’ outputs with biopsies results. When lung biopsy is not available, lung-RADS could help standardise the comparisons between the human radiologist and the machine. The field of radiology should not give up principles from the diagnostic accuracy studies, such as the choice for the correct ground truth, just because AI is used. Clear and complete reporting of the reference standard used would help radiologists trust in the performance that AI models claim to have. This review presents clear recommendations about the essential methodological aspects of diagnostic models that should be incorporated in studies using AI to help detect or segmentate lung nodules. The manuscript also reinforces the need for more complete and transparent reporting, which can be helped using the recommended reporting guidelines

AGREE-S: AGREE II extension for surgical interventions – United European Gastroenterology and European Association for Endoscopic Surgery methodological guide

Evidence; Guidelines; QualityEvidencia; Pautas; CalidadEvidència; Pautes; QualitatBackground The Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument has been developed to inform the methodology, reporting and appraisal of clinical practice guidelines. Evidence suggests that the quality of surgical guidelines can be improved, and the structure and content of AGREE II can be modified to help enhance the quality of guidelines of surgical interventions. Objective To develop an extension of AGREE II specifically designed for guidelines of surgical interventions. Methods In the tripartite Guideline Assessment Project (GAP) funded by United European Gastroenterology and the European Association for Endoscopic Surgery, (i) we assessed the quality of surgical guidelines and we identified factors associated with higher quality (GAP I); (ii) we applied correlation analysis, factor analysis and the item response theory to inform an adaption of AGREE II for the purposes of surgical guidelines (GAP II); and (iii) we developed an AGREE II extension for surgical interventions, informed by the results of GAP I, GAP II, and a Delphi process of stakeholders, including representation from interventional and surgical disciplines; the Guideline International Network (GIN); the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group; the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) initiative; and representation of surgical journal editors and patient/public. Results We developed AGREE-S, an AGREE II extension for surgical interventions, which comprises 24 items organized in 6 domains; Scope and purpose, Stakeholders, Evidence synthesis, Development of recommendations, Editorial independence, and Implementation and update. The panel of stakeholders proposed 3 additional items: development of a guideline protocol, consideration of practice variability and surgical/interventional expertise in different settings, and specification of infrastructures required to implement the recommendations. Three of the existing items were amended, 7 items were rearranged among the domains, and one item was removed. The domain Rigour of Development was divided into domains on Evidence Synthesis and Development of Recommendations. The new domain Development of Recommendations incorporates items from the original AGREE II domain Clarity of Presentation. Conclusion AGREE-S is an evidence-based and stakeholder-informed extension of the AGREE II instrument, that can be used as a guide for the development and adaption of guidelines on surgical interventions.The Guideline Assessment Project (GAP) III received financial support from the United European Gastroenterology (UEG) and the European Association for Endoscopic Surgery and Other Interventional Techniques (EAES), both non-profit organizations. The funders had no role in the design or development of this project

Open science practices need substantial improvement in prognostic model studies in oncology using machine learning

Objective: To describe the frequency of open science practices in a contemporary sample of studies developing prognostic models using machine learning methods in the field of oncology. Study design and setting: We conducted a systematic review, searching the MEDLINE database between December 1, 2022, and December 31, 2022, for studies developing a multivariable prognostic model using machine learning methods (as defined by the authors) in oncology. Two authors independently screened records and extracted open science practices. Results: We identified 46 publications describing the development of a multivariable prognostic model. The adoption of open science principles was poor. Only one study reported availability of a study protocol, and only one study was registered. Funding statements and conflicts of interest statements were common. Thirty-five studies (76%) provided data sharing statements, with 21 (46%) indicating data were available on request to the authors and seven declaring data sharing was not applicable. Two studies (4%) shared data. Only 12 studies (26%) provided code sharing statements, including 2 (4%) that indicated the code was available on request to the authors. Only 11 studies (24%) provided sufficient information to allow their model to be used in practice. The use of reporting guidelines was rare: eight studies (18%) mentioning using a reporting guideline, with 4 (10%) using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis statement, 1 (2%) using Minimum Information About Clinical Artificial Intelligence Modeling and Consolidated Standards Of Reporting Trials-Artificial Intelligence, 1 (2%) using Strengthening The Reporting Of Observational Studies In Epidemiology, 1 (2%) using Standards for Reporting Diagnostic Accuracy Studies, and 1 (2%) using Transparent Reporting of Evaluations with Nonrandomized Designs. Conclusion: The adoption of open science principles in oncology studies developing prognostic models using machine learning methods is poor. Guidance and an increased awareness of benefits and best practices of open science are needed for prediction research in oncology

AGREE-S : AGREE II extension for surgical interventions - United European Gastroenterology and European Association for Endoscopic Surgery methodological guide

The Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument has been developed to inform the methodology, reporting and appraisal of clinical practice guidelines. Evidence suggests that the quality of surgical guidelines can be improved, and the structure and content of AGREE II can be modified to help enhance the quality of guidelines of surgical interventions. To develop an extension of AGREE II specifically designed for guidelines of surgical interventions. In the tripartite Guideline Assessment Project (GAP) funded by United European Gastroenterology and the European Association for Endoscopic Surgery, (i) we assessed the quality of surgical guidelines and we identified factors associated with higher quality (GAP I); (ii) we applied correlation analysis, factor analysis and the item response theory to inform an adaption of AGREE II for the purposes of surgical guidelines (GAP II); and (iii) we developed an AGREE II extension for surgical interventions, informed by the results of GAP I, GAP II, and a Delphi process of stakeholders, including representation from interventional and surgical disciplines; the Guideline International Network (GIN); the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group; the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) initiative; and representation of surgical journal editors and patient/public. We developed AGREE-S, an AGREE II extension for surgical interventions, which comprises 24 items organized in 6 domains; Scope and purpose, Stakeholders, Evidence synthesis, Development of recommendations, Editorial independence, and Implementation and update. The panel of stakeholders proposed 3 additional items: development of a guideline protocol, consideration of practice variability and surgical/interventional expertise in different settings, and specification of infrastructures required to implement the recommendations. Three of the existing items were amended, 7 items were rearranged among the domains, and one item was removed. The domain Rigour of Development was divided into domains on Evidence Synthesis and Development of Recommendations. The new domain Development of Recommendations incorporates items from the original AGREE II domain Clarity of Presentation. AGREE-S is an evidence-based and stakeholder-informed extension of the AGREE II instrument, that can be used as a guide for the development and adaption of guidelines on surgical interventions

ACCORD (ACcurate COnsensus Reporting Document): a reporting guideline for consensus methods in biomedicine developed via a modified Delphi

Background: In biomedical research, it is often desirable to seek consensus among individuals who have differing perspectives and experience. This is important when evidence is emerging, inconsistent, limited, or absent. Even when research evidence is abundant, clinical recommendations, policy decisions, and priority-setting may still require agreement from multiple, sometimes ideologically opposed parties. Despite their prominence and influence on key decisions, consensus methods are often poorly reported. Our aim was to develop the first reporting guideline dedicated to and applicable to all consensus methods used in biomedical research regardless of the objective of the consensus process, called ACCORD (ACcurate COnsensus Reporting Document). Methods and findings: We followed methodology recommended by the EQUATOR Network for the development of reporting guidelines: a systematic review was followed by a Delphi process and meetings to finalize the ACCORD checklist. The preliminary checklist was drawn from the systematic review of existing literature on the quality of reporting of consensus methods and suggestions from the Steering Committee. A Delphi panel (n = 72) was recruited with representation from 6 continents and a broad range of experience, including clinical, research, policy, and patient perspectives. The 3 rounds of the Delphi process were completed by 58, 54, and 51 panelists. The preliminary checklist of 56 items was refined to a final checklist of 35 items relating to the article title (n = 1), introduction (n = 3), methods (n = 21), results (n = 5), discussion (n = 2), and other information (n = 3). Conclusions: The ACCORD checklist is the first reporting guideline applicable to all consensus-based studies. It will support authors in writing accurate, detailed manuscripts, thereby improving the completeness and transparency of reporting and providing readers with clarity regarding the methods used to reach agreement. Furthermore, the checklist will make the rigor of the consensus methods used to guide the recommendations clear for readers. Reporting consensus studies with greater clarity and transparency may enhance trust in the recommendations made by consensus panels

Reporting guidelines used varying methodology to develop recommendations

Background and Objectives We investigated the developing methods of reporting guidelines in the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network's database. Methods In October 2018, we screened all records and excluded those not describing reporting guidelines from further investigation. Twelve researchers performed duplicate data extraction on bibliometrics, scope, development methods, presentation, and dissemination of all publications. Descriptive statistics were used to summarize the findings. Results Of the 405 screened records, 262 described a reporting guidelines development. The number of reporting guidelines increased over the past 3 decades, from 5 in the 1990s and 63 in the 2000s to 157 in the 2010s. Development groups included 2–151 people. Literature appraisal was performed during the development of 56% of the reporting guidelines; 33% used surveys to gather external opinion on items to report; and 42% piloted or sought external feedback on their recommendations. Examples of good reporting for all reporting items were presented in 30% of the reporting guidelines. Eighteen percent of the reviewed publications included some level of spin. Conclusion Reporting guidelines have been developed with varying methodology. Reporting guideline developers should use existing guidance and take an evidence-based approach, rather than base their recommendations on expert opinion of limited groups of individuals

AGREE-S: AGREE II extension for surgical interventions - United European Gastroenterology and European Association for Endoscopic Surgery methodological guide

The Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument has been developed to inform the methodology, reporting and appraisal of clinical practice guidelines. Evidence suggests that the quality of surgical guidelines can be improved, and the structure and content of AGREE II can be modified to help enhance the quality of guidelines of surgical interventions

Factors affecting compliance with the measles vaccination schedule in a Brazilian city

CONTEXT AND OBJECTIVE: The success of vaccination campaigns depends on the degree of adherence to immunization initiatives and schedules. Risk factors associated with children's failure to receive the measles vaccine at the correct age were studied in the city of São Paulo, Brazil. DESIGN AND SETTING: Case-control and exploratory study, in the metropolitan area of São Paulo. METHODS: The caregivers of 122 children were interviewed regarding their perceptions and understanding about the measles vaccination and the disease. RESULTS: The results showed that age, region of residence, marital status and education level were unrelated to taking measles vaccines adequately. Most individuals remembered being informed about the last annual vaccination campaign by television, but no communication channel was significantly associated with vaccination status. The answers to questions about knowledge of the disease or the vaccine, when analyzed alone, were not associated with taking measles vaccinations at the time indicated by health agencies. The results showed that, when parents felt sorry for their children who were going to receive shots, they delayed the vaccination. Most of the children did not take the measles vaccination on the exactly recommended date, but delayed or anticipated the shots. CONCLUSION: It is clear that there is no compliance with the government's recommended measles vaccination schedule (i.e. first dose at nine and second at 15 months of age, as recommended in 1999 and 2000). Feeling sorry for the children receiving shots can delay vaccination taking